Urban Energy Demand Research Articles

Models for generating place and time dependent urban energy demand profiles

In this paper, we present a new model for generating spatiotemporal power demand data for urban areas of the form P(x,y,t). The model is flexible and can be adjusted to different cases and local conditions. The dimensions of the model are not restricted, but a typical case would comprise an hour-by-hour simulation over a whole year with a spatial resolution from a few hundred meters up to several kilometers, depending on the area to be covered. These kinds of load profiles are useful when analyzing, e.g., smart grids, demand side management, and renewable energy in the urban context. The model was applied to two cities, Helsinki with detailed input data available, and Shanghai with access to rough data only. In both cases, the generated load patterns appeared logical in terms of empirical observations on how power demand behaves in space and time.

Assessing Passive and Active Solar Energy Resources in Cities Using 3D City Models

Many cities today are committed to increasing the energy efficiency of buildings and the fraction of renewables. However, quantitative data on urban energy performance are rarely available during the design stage of new towns or for rehabilitation scenarios of existing cities.Three dimensional city models based on the spatio-semantic data format CityGML offer powerful new methods for the quantitative evaluation of urban energy demand and costs, and simultaneously allow the simulation of renewable energy systems. Such a ‘semantically enriched’ models was used in this work for energy demand diagnostics, refurbishment forecast and renewable supply scenarios.A case study was done using this method in an existing urban quarter in Ludwigsburg/Germany. Based on its three dimensional representation, the photovoltaic potential has been calculated and compared with the electricity demand to establish the photovoltaic fraction. On the thermal side, the passive solar gains were simulated for each building in the city quarter to analyse the solar contribution for heating demand reduction. The simulations were validated with measured gas consumptions. Some rehabilitation scenarios have also been simulated. In such a moderately dense post-war district, the calculated energy savings potential reach in total 65%, equally distributed between heat savings following building envelope refurbishment, and electricity savings due to the installation of PV on the roofs.

Bringing it all together: researcher dialogue to improve synthesis in regional climate adaptation in South-East Queensland, Australia

The effectiveness of climate adaptation policies in one sector can be compromised or aided by policies developed in another sector. When the focus of adaptation is a single geographical region, this potential for interaction between sectoral policies is heightened due to spatial, political and functional proximities. This paper analyses interactions within three suites of climate adaptation options developed for Australia’s ‘South-East Queensland’ region relating to: (1) wetland migration, coastal infrastructure and planned retreat; (2) urban water security and energy demand; and (3) terrestrial biodiversity and agricultural viability. Using the concept of ‘institutional interplay’ to structure a process of dialogue amongst researchers, we identify a number of critical implementation requirements for successful regional-scale adaptation. There is a need for greater focus on neighbourhood or sub-regional scales of policy design and intervention, particularly for the coordination of adapted infrastructure and services to households. Policy-makers must also be more explicit in considering broader drivers of land-use change and economic adjustment likely to impact on proposed adaptations. In considering these issues, our paper also demonstrates a process for conducting cross-sectoral syntheses that can be employed in other regional-scale adaptation studies.

Development of an urban energy demand forecasting system to support environmentally friendly urban planning

This study proposes a new urban energy demand forecasting system that includes the following improvements: (a) a facility planning information database (DB), (b) an energy and planning statistics DB, and (c) an enhancement of the accuracy of the energy calculation method. Each of these improved aspects is involved in energy demand forecasting for urban planning. The results from this study are as follows.(1).An Environment and energy Geographical Information System Database (E-GIS DB), which provides the mesh unit facility information, was utilized to allow for the forecasting and control of urban energy demands for each unit space.(2).An energy consumption unit figure was connected with an energy simulation to diversify the level of the urban energy consumption sector and the primary energy into hourly information. This figure allows for more accurate demand forecasting.(3).Urban facilities were categorized according to energy use characteristics and were modeled to allow for energy demand forecasts.(4).The energy demand was considered in an urban climate during summer with the characteristics of the heating methods that are suitable for domestic circumstances. Thus, a separate algorithm was suggested for a cooling period and a heating/intermission period to enhance the accuracy of the demand forecasts.(5).The performance of this energy demand forecasting system was validated, such that excessively high or low calculated values can be modified from the current method in a ‘planned city’ while the urban energy demand can be forecasted relatively correct and in detail with differences of a factor of 0.20–0.44 for the cooling period in the ‘existing city’.(6).The proposed urban energy demand forecasting system was constructed as EnerISS Solver which is an automated module. This module drastically reduced time consuming for predicting energy demand and urban climate to respond for the urban energy planning subjects’ needs immediately.

Smart Sustainable Cities: An Integrated Planning Approach towards Sustainable Urban Energy Systems, India

Cities denote instantaneously a challenge and an opportunity for climate change policy. Cities are the place where most energy services are needed because urbanization is closely linked to high population densities and concentration of economic activities and production (Urban energy demand). Consequently, it is critical to explain about the role of cities within the world's energy systems and its correlation with the climate change issue. With more than half of the world's population already living in urban areas, and that percentage expected to rise to 75 per cent by 2050, it is clear that the path to sustainable development must pass through cities. Cities expanding in size and population pose increased challenges to the environment, of which energy is part as a natural resource, and to the quality of life. Nowadays, most cities have already understood the importance of sustainability, both at their local scale as in terms of their contribution to sustainability at higher geographical scales. It requires the perception of a as a complex and dynamic ecosystem, an open system, or cluster of systems, where the energy as well as the other natural resources is transformed to satisfy the needs of the different urban activities. In fact, buildings and transportation generally represent most of cities direct energy demand, i.e., between 60 per cent and 80 per cent of the overall consumption. Buildings, both residential and services are usually influenced by the local physical and social conditions. In terms of transport, the energy demand is also strongly linked with the specific characteristics of a (urban mobility).The concept of a city builds on statistics as seven key axes of a city's success in moving towards common platform (brain nerve)of sustainable urban energy systems. With the aforesaid knowledge, the authors have suggested a frame work to role of cities, as energy actors for smart management. The authors have discusses the potential elements needed for energy in smart cities and also identified potential energy actions and relevant barriers. Furthermore, three levels of smartness in cities actions to overcome market /institutional failures with a local approach are distinguished. The authors have made an attempt to conceive and implement concepts of smartness by adopting the or local government as nerve center through an integrated planning approach. Finally, concluding with recommendations for the organization of the Smart Sustainable Cities for positive changes of urban India.

The Other Energy Crisis: Managing Urban Household Energy Use in Senegal

The persistent and growing demand for woodfuels in devel­ oping countries constitutes an important, often ign ored resource and environmental problem. To gauge the impact ofthis other energy crisis, the case ofSenegal in the 1990s is assessed, focusing on the important urban household sub­ sector. A disagrg egated database is used to highlight the problems of increasing urban energy demand met by unsus­ tainable rural woodfuel supply, and the inadequacy of exist­ ing policies and programs. A flexible, consumer-oriented strategy is recommended, based on biomass supply system management, interfuel substitution, conservation, and a sound pricing policy.

Assessment of Urban Heat Island and Energy Demand Parameters in Akure, Nigeria

The Kenya Meteorological Society (KMS) is a non-profit making professional/ scientific society, in a bid to promote the understanding of meteorology and its applications, among other functions, in Kenya and beyond.

Planning 0-Energy Cities Using Local Energy Sources

The world is urbanizing rapidly and urban resources demand is increasing. Cities depend highly on foreign fossil energy sources. Incoming resources are used inefficiently, only part of energy input is used and remaining is wasted. To reduce dependency and increase self-sufficiency, cities have to search for local and renewable energy sources. Cities are a reservoir of untapped energy sources. Cities can support themselves to reach 0-energy status and to become independent. Cities have unused space available to capture incoming energy. Several technologies are available, but not widely implemented. Therefore, further effort should focus on planning and implementing those technologies. And urban planning should support resources management. Proposed method, based on Urban Harvest concept and exergy principle, towards planning 0-energy cities, consists of five steps. It gives an overview of urban energy demand and potential supply, and describes how supply and demand can be coupled effectively.

3D City modeling for urban scale heating energy demand forecasting

An urban energy management tool was developed, which is able to predict the heating energy demand of urban districts and analyze strategies for improving building standards. Building models of different Levels of Detail are investigated and analyzed according to their suitability for forecasting energy demand. Based on the specific 3D city model, an input file is generated, which can be read by the building simulation model. Special focus is put on a method for modeling the heating energy demand of the buildings with the fewest input parameters possible, but one which will give reliable forecast results. A simple transmission heat loss method and an energy-balance method were tested. In both cases, there was a good correlation between the measured and calculated annual values for a case study area of over 700 buildings in Ostfildern, Germany. The results also show that a 3D city model (with low geometrical detail) can be used for energy demand forecasting on an urban scale.

CONCEPTUALIZATION OF URBANIZATION STRUCTURE AND CLIMATE CHANGE IN LAGOS, NIGERIA

Urbanization is synonymous with environmental challenges. In developing countries, the challenges have assumed higher dimensions proportionally due to multifarious issues of rapid changes in the environment, due to development, through population growth and industrialization, and accompanied by all kinds of pollution such as air pollution, waste disposal, land use degradation, and vehicular pollution as the resultant effects of man’s interaction with the environment. The main characteristic effect is the raised temperature of the city centre (UHI) leading to excessive energy use for cooling and putting urban population at great morbidity and mortality risks. This paper literally explores the conceptual framework of interaction between urbanization structure and understanding social impacts of climate change and variability for the evaluation of strategies in the urbanized environment that might serve as adaptive response to climate change. The urbanization structure that affects Lagos state is discussed in relation to the location of the city, the size, the population density, urban geometry, thermal property, air pollution, land use pattern, wind speed and anthropogenic activities. The study revealed that climate change is posing increasing challenges for cities placing greater stress and impacts on multiple social and biophysical systems, including urban infrastructure, water and energy demand simultaneously, followed by a strong global trend towards urbanization of urban poverty. The study concluded that climate change has impacted greatly on virtually all the socio-economic aspects of man.

Impacts of urbanization on urban structures and energy demand: What can we learn for urban energy planning and urbanization management?

Abstract Since 2007, for the first time in human history, more than half of the world's population has been living in cities. The urbanization process is a key phenomenon of economic development, and leads to a significant concentration of human resources, economic activities, and resource consumption in cities. Although covering only about 2% of the earth's surface, cities are responsible for about 75% of the world's consumption of resources. This trend will intensify over the next decades as a consequence of high urbanization rates in Africa and, even more importantly, in Asia. In order to estimate the impact of urbanization on energy demand, we have to identify the different processes and mechanisms of urbanization that substantially affect urban structures as well as human behavior. Taking a closer look at city-related production, mobility and transport, infrastructure and urban density, as well as private households, we find that various mechanisms of urbanization within the different sectors of the economy lead to a substantial increase in urban energy demand and to a change in the fuel mix. The relevance of these mechanisms differs considerably between developed and developing countries as well as within the group of developing countries. Over the next decades, cities and especially newly emerging megacities in developing countries will play a key role concerning the development and distribution of global energy demand. Hence, urban energy planning and urbanization management will be pivotal for creating the right framework conditions for a sustainable energy future.

Evaluating the effectiveness of urban energy conservation and GHG mitigation measures: The case of Xiamen city, China

To assess the effectiveness of urban energy conservation and GHG mitigation measures, a detailed Long-range Energy Alternatives Planning (LEAP) model is developed and applied to analyze the future trends of energy demand and GHG emissions in Xiamen city. Two scenarios have been designed to describe the future energy strategies in relation to the development of Xiamen city. The ‘Business as Usual’ scenario assumes that the government will do nothing to influence the long-term trends of urban energy demand. An ‘Integrated’ scenario, on the other hand, is generated to assess the cumulative impact of a series of available reduction measures: clean energy substitution, industrial energy conservation, combined heat and power generation, energy conservation in building, motor vehicle control, and new and renewable energy development and utilization. The reduction potentials in energy consumption and GHG emissions are estimated for a time span of 2007–2020 under these different scenarios. The calculation results in Xiamen show that the clean energy substitution measure is the most effective in terms of energy saving and GHG emissions mitigation, while the industrial sector has the largest abatement potential.

Monitoring urban transport air pollution and energy demand in Rawalpindi and Islamabad using leap model

A research associated with urban transportation was carried out in Rawalpindi and Islamabad to analyze the status of emission of air pollutants and energy demands. The study included a discussion of past trends and future scenarios in order to reduce the future emissions. A simple model of passenger transport has been developed using computer based software called Long-Range Energy Alternatives Planning System (LEAP). The LEAP model was used to estimate total energy demand and the vehicular emissions for the base year 2000 and extrapolated till 2030 for the future predictions. Transport database in Rawalpindi and Islamabad, together with fuel consumption values for the vehicle types and emission factors of NOx, SO2 and PM10 corresponding to the actual vehicle types, formed the basis of the transport demand, energy consumption and total emission calculations. Apart from base scenario, the model was run under three alternative scenarios to study the impact of different urban transport policy initiatives that would reduce energy demand and emissions in transport sector of Rawalpindi and Islamabad. The prime objective was to arrive at an optimal transport policy, which limits the future growth of fuel consumption as well as air pollution.

Prediction of Residential Building Energy Consumption in Jilin Province, China

This research investigates and analyzes the current condition of urban and rural residential energy consumption of Jilin Province, China, by establishing a model of residential energy demand. The model can predict such energy demand based on the demand types and environmental load of Jilin Province until 2020. Compared with 2000, rural residential energy demand will reduce approximately 25% in 2020, because of the decrease of rural population per household, while the urban residential energy demand will grow about 2.5 times in 2020, because of the increased urban population and rising standard of living. At the same time, compared with 2000, CO2 emissions resulting from rural residential energy consumption will grow approximately 10% in 2020. The basic reason for this is the increase of electricity consumption by rural residents. CO2 emissions from urban residential energy consumption will grow about three times in 2020.

Modeling and Future Scenario Setting of Urban Energy Demand Based on District Energy System

Modeling and Future Scenario Setting of Urban Energy Demand Based on District Energy System

06/01031 Sustainable cities — modelling urban energy supply and demand: Brownsword, R. A. et al. Applied Energy, 2005, 82, (2), 167–180.

06/01031 Sustainable cities — modelling urban energy supply and demand: Brownsword, R. A. et al. Applied Energy, 2005, 82, (2), 167–180.

Modeling and Future Scenario Setting of Urban Energy Demand Based on District Energy System

本論文では、都市を500m四方のメッシュからなる地区に分解した上で、地区を床面積の特性に基づいて類型化し、各類型について選んだ代表地区について、現地調査等から得られた情報を反映した詳細なエネルギー消費シミュレーションをおこなう手法により、2050年を目標とした民生業務部門の省エネルギー・二酸化炭素排出削減対策の定量的評価をおこなった。本手法をとることにより、従来の建物レベルの対策効果を都市域に積み上げる手法に対し、地域冷暖房システムの導入効果や、都市内の町並みの特性を活かした対策の評価が可能になった。シミュレーション結果より、電源の二酸化炭素排出原単位の変化に大きく左右されるものの、現在の高密度地区のみに高効率な地域冷暖房を整備した場合と、低密度地区の建築ストックを大胆な土地利用転換により高密度地区に集積させた場合のCO2排出削減ポテンシャルを定量的に示すことが出来た。また、集積マネージメントしない場合には、小規模建築の着実な省エネルギー対策の実施が大きな課題になることを示した。

Sustainable cities – modelling urban energy supply and demand

A model of urban energy consumption has been developed using energy supply data and post-code information. The model simulates spatial and diurnal variations in energy demand, and also models the effect of energy-management measures and associated reductions in CO 2 emissions. A linear programming optimisation module is used to identify the most cost-effective measures to achieve specified CO 2 or energy reduction-targets. When combined with data from an associated attitudinal survey, the model can be used to assess the potential for CO 2 reduction in the urban environment.

Methods of predicting urban domestic energy demand with reduced datasets: a review and a new GIS-based approach

This paper reviews existing bottom-up approaches to the urban scale prediction of domestic energy demand and introduces a new approach based on Geographical Information Systems (GIS). It describes how software tools can be used to derive predictors from the plan form of dwellings extracted from digital maps and, using a new default-data system, to satisfy the large data requirements of an embedded version of the BREDEM-8 domestic energy model. Energy consumption and CO2emissions of urban dwellings can be predicted quickly and robustly without costly on-site measurements or statistically derived geometrical models. Urban areas of almost arbitrary size can be modelled and accuracy can be incrementally improved with additional data. The model is validated by comparison with results produced by the UK's National Home Energy Rating scheme software using complete site-surveyed datasets. Its ability to rapidly estimate energy demand is demonstrated for around 400 dwellings in Leicester, UK using only the dwelling age, the default data system and the GIS tools.

Contribution to the analysis of urban residential electrical energy demand in developing countries

Access of large segments of the population to electrical energy continues to be limited in the cities of developing countries where the standards pertaining to installed power and consumption are ill suited to the level of appliances owned by households. In this paper, a new evaluation method of residential users’ actual needs in electricity is proposed for Cameroon. The approach is based on the determination of the nature, number and power of the appliances, as well as their operation periods. The method used is a survey administered to a representative sample of households. A detailed questionnaire appraises specific consumption and installed power and is also used to construct the households’ load curve. The need for electrical energy varies according to the size of the city and, inside the city, to household income. The average power used per dwelling accounts for less than half the value prescribed by current norms. If implemented, the method would help optimise network investments and operation. The load curve obtained in the experiment shows that the peak output power is recorded in the evening and that household demand makes up most of this charge. The proposed strategy would reduce electrical energy costs, thus being of great potential interest for poor urban populations.